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- Automatically finds negative user feedback and generates better
answers
- All tasks work with the same FeedbackEnrichment DataPoint that gets
filled out as it moves through the memify pipeline
- Creates new nodes and edges in the knowledge graph, linking improved
answers back to the original feedback and interactions
- Includes a complete example showing how to set up a conversation, ask
questions, submit feedback, and run the enrichment pipeline when answers
are wrong
## Type of Change
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- [ ] Bug fix (non-breaking change that fixes an issue)
- [x] New feature (non-breaking change that adds functionality)
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In `uv.lock`, we've already been using fastapi version 0.119.0 for a
while.
However, with #1586 changes we can't allow fastapi to be lower than
0.116.2.
See https://github.com/fastapi/fastapi/pull/14077
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`LocalFileStorage.store(...)` when storing strings, uses system defaults
for newlines.
It is universally `\n` in Unix and MacOS, but for Windows by default its
`\r\n` (ancient Windows standard)
This results in hash mismatch, although content is identical.
Windows can work with `\n`, so this PR explicitly uses `\n` for newline
encoding
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## Description
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Logs are getting polluted with these starlette deprecation warnings.
This PR replaces the depracated status code
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## Description
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This PR reruns notebooks with latest cognee and updates outputs
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This PR is an iteration over #1552:
1. Refactors `preferred_loaders` from dicts, to a list that can contain
strings (name of the loader) or dicts (`{loader_name: {arg1: val1}}`),
i.e. - `[{"loader_name_one": {"arg1": "val1"}}, "loader_name_two"]`
2. Adds default extraction rules for html parsing
3. Adds unit tests that cover the changes + unit test for tavily
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## Description
#1548 did not handle multi-tenant case, where graph db context is set
further downstream.
This version adds empty graph logging/handling that works for
multi-tenant case
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Changes temporal test secrets
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## Description
While testing Cognee with the latest version of Ollama, I discovered two
breaking changes that prevented proper functionality:
1. **Ollama API key change**: The embeddings API response key has been
updated from `embedding` to `embeddings` in newer Ollama versions
2. **Vector dimension handling**: The `create_lance_data_point` method
was receiving vectors as nested lists `[[...]]` instead of a flat list.
Added validation to flatten the vector when this occurs.
These changes ensure compatibility with the latest Ollama release while
maintaining the expected behavior.
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The model, endpoint, and API key for BAML tests were changed because
they had issues with the new endpoint. Now they use OpenAI.
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